影响力指数
论文质量、代表作、近期表现、广度与样本量置信度综合计算
62.49/100
前 4.1%
全站排名 #2,668
发表论文7 篇
平均评分
年均产出2.3 篇/年
Yam Eitan
研究方向
Geometric Deep Learning · Graph Neural Networks · Learning under symmetries · convex geometry
16
Topological Blindspots: Understanding and Extending Topological Deep Learning Through the Lens of Expressivity
ICLR 2025Oral
一作23
GradMetaNet: An Equivariant Architecture for Learning on Gradients
NeurIPS 2025Poster
二作13
Balancing Efficiency and Expressiveness: Subgraph GNNs with Walk-Based Centrality
ICML 2025Poster
二作24
Balancing Efficiency and Expressiveness: Subgraph GNNs with Walk-Based Centrality
ICLR 2025Rejected
二作